Perfluoroalkyl substances (PFAS) phytoremediation by manipulating soil properties and plant management

ABSTRACT

Phytoremediation processes, methods, materials and compositions to remediate soil, sediment and groundwater that is contaminated by per- and polyfluoroalkyl substances (PFAS) via phytoextraction which includes the uptake and translocation of contaminants in the contaminated media by plant roots into the above ground portions of the plants. The plants can be selected from sixteen plants as well as other plants and the invention can include managing soil salinity levels of the plants, manipulating amounts of organic matter in the contaminated site media, managing pH levels of the contaminated sites, utilizing double cropping systems, utilizing double-canopy system, and managing harvest methodology of the plants.

RELATED APPLICATIONS

This application is a Divisional Application of U.S. patent application Ser. No. 16/793,103 filed Feb. 18, 2020, now allowed, which claims the benefit of priority to U.S. Provisional Patent Application Ser. No. 62/847,634 filed May 14, 2019. The entire disclosure of each of the applications listed in this paragraph are incorporated herein by specific reference thereto.

FIELD OF INVENTION

This invention relates to phytoremediation, and in particular to phytoremediation processes, methods, materials and compositions to remediate soil, sediment and groundwater that is contaminated by per- and polyfluoroalkyl substances (PFAS) via phytoextraction which includes the uptake and translocation of contaminants in the soil by plant roots into the above ground portions of the plants.

BACKGROUND AND PRIOR ART

PFAS are a large group of synthetic compounds that have been broadly used to make various products more resistant to stains, grease, and water since the 1940s and there is mounting evidence that exposure above specific levels to certain PFAS leads to adverse health effects. Examples of products with which PFAS have been used extensively include nonstick cookware, stain resistant textiles, and waterproof clothing. They have also been used in many food packaging and firefighting materials. Because they help reduce friction, they are also used in a variety of other industries, including aerospace, automotive, building and construction, and electronics. PFAS are known to break down slowly in the environment and are characterized as persistent. Due to their pervasive use and persistence, there is widespread human exposure to PFAS including perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS).

There is a need for a viable and cost-effective phytoremediation cleanup methodology to address PFAS impacted soil, sediments, and groundwater. The methodology would be all the more desirable if it met core elements outlined in the American Society of Testing Materials (ASTM) E2893 Standard Guide for Greener Cleanups that include minimizing greenhouse gas emissions, air pollutants, use of materials, generation of waste, disturbance to land and ecosystems, and noise and light disturbance.

Current approaches to cleanup of impacted soil and sediment consists of expensive and energy consumptive excavation and removal.

In November 2016 the US EPA issued health advisories for PFOA and PFOS, based on the agency's assessment of the latest peer-reviewed science, to provide drinking water system operators, and state, tribal, and local officials who have the primary responsibility for overseeing these systems, with information on the health risks of these chemicals. With the issuance of these advisories greater focus has been brought to assessing the fate and potential remediation of PFAS in the environment. In February 2019, EPA issued a PFAS Action Plan to further understand and reduce PFAS risks to the public. The Action Plan describes EPA's approaches to addressing current PFAS contamination and specifically includes steps to propose designating PFOA and PFOS as “hazardous substances”. In addition, the plan includes developing toxicity values for perfluorobutane sulfonic acid (PFBS) and developing guidance for cleanup actions where groundwater is contaminated with PFOA and PFOS.

Studies have indicated that PFAS accumulates in plants where it is found in the soil. However, these studies have not addressed processes, methods, materials and/or compositions to effectuate greater plant uptake for the purpose of phytoremediation.

Prospects of a phytoremediation approach for cleaning up PFAS-impacted soil and sediments were evaluated in a recent study from European researchers who found various plants species to be promising candidates for phytoremediation of PFAS (Gobelius, L., J. Lewis, and I. Ahrens, 2017. Plant Uptake of Per- and Polyfluoroalkyl Substances at a Contaminated Fire Training Facility to Evaluate the Phytoremediation Potential of Various Plant Species. Environ. Sci. Technol. 2017, 51, 12602-12610). This research consisted of a survey of plants present at a site known to be contaminated by PFAS.

Other related research has investigated the presence of PFAS in agricultural crops, largely to assess potential threats posed by PFAS in food supplies. These studies showed agricultural crop plants accumulating PFAS compounds in both root and above-ground tissue at low levels (Navarro et al 2017, Ghisi et al. 2018). The amount of accumulation depends on a variety of factors including plant species (Navarro et al. 2017, Ghisi et al. 2018), PFAS group and chain length (Blaine et al. 2014, Ghisi et al. 2018), water or soil concentration (Blaine et al. 2014, Ghisi et al. 2018), organic carbon content of the soil (Blaine et al. 2014), salinity and pH (Zhao et al. 2013). More recently, Zhang et al. (2019) reported on the uptake and accumulation of seven PFAS compounds by the wetland species Juncus effuses. They reported removal efficiencies from solution as high as 11.4% for spiked PFAS, but reported little translocation to above-ground components of the plant.

These previous studies differ from the invention presented herein because our invention focused on maximizing above-ground plant accumulation and was developed via a replicated statistically-based randomized block design study within an environmentally controlled greenhouse that produced and demonstrated repeatable results forming the basis of our phytoremediation processes, methods, materials and compositions which remediate soil, sediment, and groundwater contaminated by per- and polyfluoroalkyl substances (PFAS) via phytoextraction.

SUMMARY OF THE INVENTION

A primary objective of the present invention is to provide phytoremediation processes, methods, materials, and compositions to remediate soil that is contaminated by per- and polyfluoroalkyl substances (PFAS).

A secondary objective of the present invention is to provide phytoremediation processes, methods, materials, and compositions to remediate sediment that is contaminated by per- and polyfluoroalkyl substances (PFAS).

A third objective of the present invention it to provide phytoremediation processes, methods, materials, and compositions to remediate groundwater that is contaminated by per- and polyfluoroalkyl substances (PFAS).

A fourth objective of the present invention is to maximize phytoremediation of per- and polyfluoroalkyl substances (PFAS) at contaminated sites with selected plants by managing soil salinity levels of the plants, manipulating amounts of organic matter in the contaminated media, managing pH levels of the contaminated media, and managing harvest methodology of the plants.

A fifth objective of the present invention is to maximize phytoremediation of per- and polyfluoroalkyl substances (PFAS) at contaminated sites by utilizing coordinated double cropping systems to overlap cool season and warm season plants and utilizing coordinated dual cropping systems with shade tolerant understory forbs and grasses with tree species.

A method for increasing the amount of per- and polyfluoroalkyl substances (PFAS) that a plant will accumulate from PFAS contaminated soil, sediment, and groundwater, can include the steps of growing live selected plants in per- and polyfluoroalkyl substances (PFAS) contaminated soil, sediments, or groundwater, and providing for phytoremediation via phytoextraction of the per- and polyfluoroalkyl substances (PFAS) from the contaminated media.

The providing step further includes the steps of managing soil salinity levels, manipulating amounts of organic matter in the contaminated media, using a double-cropping system, using a double-canopy system, managing pH levels of the contaminated sites and managing harvest methodology of the plants.

The live selected plant can be selected from any one of Amaranthus tricolor, Betula nigra, Brassica juncea, Cynodon dactylon, Esquisetum hyemale, Schedonorus arundinaceus, Festuca rubra (Red Fescue) and its subspecies, Helianthus annuus, Liquidambar styraciflua, Liriodendron tulipifera, Trifolium incamatum, Platanus occidentalis, and Salix nigra.

The live selected plant can be Festuca rubra (Red Fescue) and its subspecies.

The live selected plant can be Liquidambar styraciflua (Sweetgum-LP).

The live selected plant can be Salix nigra (Black willow-LP) leaves and petioles.

The step of managing soil salinity levels of the plants can include the steps of increasing soil salinity by addition of salt, other salinity-increasing soil amendments and irrigants within the range of plant tolerances.

The step of manipulating amounts of organic matter in the contaminated sites, can include the step of reducing the amounts of organic matter and soluble carbon levels in the contaminated sites.

The step of reducing the amounts of the organic matter and soluble carbon levels in the contaminated sites, can include the steps of at least one of tilling the contaminated soil and adding inorganic nitrogen to the contaminated soil.

The step of managing pH levels of the contaminated sites can include the steps of providing soil and soil-water in the contaminated media to be circumneutral (7.0 Standard Units (+/−0.5)).

The step of managing harvest methodology of the plant, can includes the steps of providing more frequent and timed harvests of the selected plant at earlier stages of growth when protein contents are greater.

The per- and polyfluoroalkyl substances (PFAS) can include the compounds of perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluorobutane sulfonic acid (PFBS).

The per- and polyfluoroalkyl substances (PFAS) can include the compounds of perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorobutane sulfonic acid (PFBS), tridecafluorohexane-1-sulfonic acid potassium salt (PFHxS), perfluoropentanoic acid (PFPeA), and undecafluorohexanoic acid (PFHxA).

The providing step can include the steps of removing significant portions of compounds of per- and polyfluoroalkyl substances (PFAS) through phytoextraction and harvesting of above ground plant tissue.

The contaminated site can be selected from at least one of PFAS contaminated soil, PFAS contaminated sediment, and PFAS contaminated groundwater.

A process for hyperaccumulating multiple per- and polyfluoroalkyl substances PFAS compounds, can include the steps of growing live selected plants in per- and polyfluoroalkyl substances (PFAS) contaminated soil, sediments, or groundwater, the live plants selected from Amaranthus tricolor, Betula nigra, Brassica juncea, Cynodon dactylon, Esquisetum hyemale, Schedonorus arundinaceus, Festuca rubra (and its subspecies), Helianthus annuus, Liquidambar styraciflua, Liriodendron tulipifera, Trifolium incamatum, Platanus occidentalis, and Salix nigra, and phytoremediating via phytoextraction of the per- and polyfluoroalkyl substances (PFAS) from the contaminated media, the PFAS contaminants including the compounds perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluorobutane sulfonic acid (PFBS).

A process for hyperaccumulating multiple per- and polyfluoroalkyl substances PFAS compounds, can include the steps of growing live selected plants in per- and polyfluoroalkyl substances (PFAS) contaminated soil, sediments, or groundwater, the live plants selected from Amaranthus tricolor, Betula nigra, Brassica juncea, Cynodon dactylon, Esquisetum hyemale, Schedonorus arundinaceus, Festuca rubra (and its subspecies), Helianthus annuus, Liquidambar styraciflua, Liriodendron tulipifera, Trifolium incamatum, and Platanus occidentalis, and Salix nigra, and phytoremediating via phytoextraction of the per- and polyfluoroalkyl substances (PFAS) from the contaminated media, the PFAS contaminants including the compounds perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorobutane sulfonic acid (PFBS), tridecafluorohexane-1-sulfonic acid potassium salt (PFHxS), perfluoropentanoic acid (PFPeA), and undecafluorohexanoic acid (PFHxA).

Further objectives and advantages of this invention will be apparent from the following detailed description of the presently preferred embodiments which are illustrated schematically in the accompanying drawings.

BRIEF DESCRIPTION OF THE FIGURES

The drawing figures depict one or more implementations in accord with the present concepts, by way of example only, not by way of limitations. In the figures, like reference numerals refer to the same or similar elements.

FIG. 1 is a flow chart summary of the phytoremediation processes, methods, materials and compositions to remediate soil, sediment, and groundwater that is contaminated by per- and polyfluoroalkyl substances (PFAS) via phytoextraction which includes the uptake and translocation of contaminants in the soil, sediment, and groundwater by plant roots into the above ground portions of the plants.

FIG. 2 are bar graphs of the Bioconcentration Factors (BCFs) of Festuca rubra (Red Fescue) for six target PFAS compounds after 24 days of initial dosing with PFAS contaminant solution.

FIG. 3 are bar graphs of the BCFs of Festuca rubra (Red Fescue) for six target PFAS compounds after 98 days of initial dosing with PFAS contaminant solution.

FIG. 4 are bar graphs of the BCFs of Cynodon dactylon (Bermudagrass) for six target PFAS compounds after 24 days of initial dosing with PFAS contaminant solution.

FIG. 5 are bar graphs of the BCFs of Cynodon dactylon (Bermudagrass) for six target PFAS compounds after 98 days of initial dosing with PFAS contaminant solution.

FIG. 6 are bar graphs of the BCFs of Liquidambar styraciflua (Sweetgum) for six target PFAS compounds after 18 days of initial dosing with PFAS contaminant solution.

FIG. 7 are bar graphs of the BCFs of Liquidambar styraciflua (Sweetgum) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 8 are bar graphs of the BCFs of Salix nigra (Black Willow) for six target PFAS compounds after 18 days of initial dosing with PFAS contaminant solution.

FIG. 9 are bar graphs of the BCFs of Salix nigra (Black Willow) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 10 are bar graphs of the BCFs of Trifolium incamatum (Crimson Clover) for six target PFAS compounds after 24 days of initial dosing with PFAS contaminant solution.

FIG. 11 are bar graphs of the BCFs of Schedonorus arundinaceus (Tall Fescue) for six target PFAS compounds after 24 days of initial dosing with PFAS contaminant solution.

FIG. 12 are bar graphs of the BCFs of Schedonorus arundinaceus (Tall Fescue) for six target PFAS compounds after 98 days of initial dosing with PFAS contaminant solution.

FIG. 13 are bar graphs of the BCFs of Brassica juncea (Mustard) for six target PFAS compounds after 24 days of initial dosing with PFAS contaminant solution.

FIG. 14 are bar graphs of the BCFs of Helianthus annuus (Sunflower) for six target PFAS compounds after 24 days of initial dosing with PFAS contaminant solution.

FIG. 15 are bar graphs of the BCFs of Amaranthus tricolor (Amaranth) for six target PFAS compounds after 67 days of initial dosing with PFAS contaminant solution.

FIG. 16 are bar graphs of the BCFs of Betula nigra (River Birch) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 17 are bar graphs of the BCFs of Esquisetum hyemale (Horsetail) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 18 are bar graphs of the BCFs of Fraxinus pennsylvanica (Green Ash) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 19 are bar graphs of the BCFs of Liriodendron tulipifera (Tulip Poplar) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 20 are bar graphs of the BCFs of Pinus taeda (Loblolly Pine) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 21 are bar graphs of the BCFs of Platanus occidentalis (Sycamore) for six target PFAS compounds after 92 days of initial dosing with PFAS contaminant solution.

FIG. 22 is a schematic of a PVC growth chamber (i.e., column) used for researching and testing plant species and soil management for PFAS phytoextraction.

FIG. 23 is a schematic of the randomized three-block study design used in the Phytoremediation Pilot Study.

In assessing the fitness of plant species to serve in a phytoremediation role by means of phytoextraction the Bioconcentration Factor (BCF) is a key metric. The BCF is calculated as the plant/soil contaminant concentration ratio: BCF_(plant) =C _(plant) /C _(reference media)

A BCF that is >1 is considered to indicate accumulation. For use in a phytoextraction context it is ideal for remedial plants to have a BCF of 10 or more. FIGS. 2 through 22 present bar graphs showing the calculated BCFs for each of six different species based on the successful bench study that established “Proof-of-Concept”. These BCFs substantiate efficacy of one or more implementations in accord with the present concepts, by way of example only, not by way of limitations.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Before explaining the disclosed embodiments of the present invention in detail, it is to be understood that the invention is not limited in its applications to the details of the particular arrangements shown since the invention is capable of other embodiments. Also, the terminology used herein is for the purpose of description and not of limitation.

In the Summary above and in the Detailed Description of Preferred Embodiments and in the accompanying drawings, reference is made to particular features (including method steps) of the invention. It is to be understood that the disclosure of the invention in this specification does not include all possible combinations of such particular features. For example, where a particular feature is disclosed in the context of a particular aspect or embodiment of the invention, that feature can also be used, to the extent possible, in combination with and/or in the context of other particular aspects and embodiments of the invention, and in the invention generally. In this section, some embodiments of the invention will be described more fully with reference to the accompanying drawings, in which preferred embodiments of the invention are shown.

This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will convey the scope of the invention to those skilled in the art. Like numbers refer to like elements throughout, and prime notation is used to indicate similar elements in alternative embodiments.

Other technical advantages may become readily apparent to one of ordinary skill in the art after review of the following figures and description.

It should be understood at the outset that, although exemplary embodiments are illustrated in the figures and described below, the principles of the present disclosure may be implemented using any number of techniques, whether currently known or not. The present disclosure should in no way be limited to the exemplary implementations and techniques illustrated in the drawings and described below.

Unless otherwise specifically noted, articles depicted in the drawings are not necessarily drawn to scale.

Phytoremediation is the direct use of living plants for in situ remediation of contaminated soil, sludges, sediments, and groundwater through contaminant removal, degradation, or containment. Phytoextraction, also called phytoaccumulation, refers to the uptake and translocation of contaminants in the soil by plant roots into the aboveground portions of the plants. Our study successfully achieved Proof-of-Concept for multiple plant species via a bench study investigation signaling the development of an effective phytoremediation process and methodology for the cleanup of PFAS in soil, sediment, and groundwater.

Based on our laboratory data, our Phase I SBIR phytoremediation innovation has verified hyperaccumulation of multiple PFAS compounds after 24 and 98 days of initiating contaminant dosing with the PFAS contaminant solution at multiple contaminant concentrations. Additionally, our work has shown repeatable trends across three plant species indicating soil management of salinity has shown a corresponding higher plant accumulation of PFAS.

Materials and Methods

Based on our knowledge of PFAS, vegetation growing vigorously within the wetted field areas of land treatment sites where PFAS-containing wastewater has historically been applied, and plants known to be efficient at phytoextraction of various contaminants, NAI selected the sixteen species for bench trial pilot study evaluation (Table 1).

TABLE 1 Selected Plant Species for Phase I SBIR Study. Scientific Name Common Name Amaranthus tricolor Amaranth Betula nigra River Birch Brassica juncea Mustard Cynodon dactylon Bermudagrass Esquisetum hyemale Horsetail Schedonorus arundinaceus Tall Fescue Festuca rubra Red Fescue Fraxinus pennsylvanica Green ash Helianthus annuus Sunflower Liquidambar styraciflua Sweetgum Liriodendron tulipifera Tulip Poplar Trifolium incarnatum Crimson Clover Pinus taeda Loblolly Pine Philopterids hexagonopter Broad Beech Fern Platanus occidentalis Sycamore Salix nigra Black Willow

Seedlings were planted in columns containing washed sand. Each column was constructed of cut polyvinylchloride (PVC) pipe that was capped at the bottom and linked by an outlet valve for collection of leachate and control of the water level within the column. The outlet valve tubing was made of clear silicone so water levels in column could be monitored via the clear tubing to assess whether fluid levels in the columns were too high or low. Washed sand meeting ASTM C33 gradation standard was used to reduce contaminant sorption. A sample of the sand was analyzed by the University of Georgia Agricultural and Environmental Services Soil, Plant, and Water Laboratory for agricultural parameters. Table 2 summarizes the soil test data.

TABLE 2 Agricultural soil test data for the washed sand growth media. % S.U. Base meq/100 g Mehlich 1 mg/kg (ppm) μS/cm pH Saturation CEC Ca Fe K Mg Mn Na Ni P Zn Ec 5.91 92.77 0.30 37.70 52.17 6.14 7.15 19.24 3.53 0.05 1.61 1.07 50

The dimensions of the columns were such that each column was filled with approximately 6000 cubic centimeters (cm³) of sand which approximately equates to approximately 9000 grams (g) at a bulk density of approximately 1.5 cubic centimeters per gram (cm3/g) (FIG. 22).

The pilot study was located in a secured greenhouse that was temperature controlled at 25±3° C. and with a relative humidity target range of 70±5%. Supplemental lighting was used to extend day length to approximately 16 hours during the autumn and winter experimental periods in an attempt to help break dormancy. Experimental units were allocated in a randomized three-block design. Blocks were physically located to distribute the treatments and replications over the greenhouse micro environmental conditions. However, block design randomization was coordinated such that the tree species and herbaceous species were randomized separately to minimize canopy interference among taller tree species versus lower growing grasses and forbs (FIG. 23).

The four plant species having the highest salt tolerance (Salix nigra, Liqudambar styraciflua, Festuca rubra, Cynodon dactylon) were also treated in separate additional experimental units utilizing a saline irrigant. The saline irrigant was comprised of a solution of approximately 2.5 grams per liter (g/L) gypsum (CaSO₄.2H₂O) and approximately 5 g/L of Epsom salt (MgSO₄.2H₂O) mixed with deionized water. This water quality had an approximate electrical conductivity of approximately 4.5 decisiemens per centimeter (dS/cm). Thus, a total number of 36 experimental units comprised each block (FIG. 23).

The contaminant dosing solution was a deionized aqueous mix containing approximately 1 milligram per liter (mg/L) of each of the following seven compounds:

1) tridecafluorohexane-1-sulfonic acid potassium salt (PFHxS)

2) heptadecafluoro-1-octanesulfonic acid (PFOS)

3) perfluorooctanoic acid (PFOA)

4) perfluoropentanoic acid (PFPeA)

5) undecafluorohexanoic acid (PFHxA)

6) nonafluoro-1-butanesulfonic acid (PFBS)

7) n-methyl perfluorooctane sulfonamide (MeFOSA)

The prepared contaminant solution was sampled using laboratory provided water sampling vials and a clean pair of nitrile gloves. The sample was shipped via overnight courier to Eurofins TestAmerica laboratory in West Sacramento, Calif. The laboratory reported concentrations (in units of nanograms per liter (ng/L) of the analytes as shown in Table 3.

TABLE 3 PFAS concentrations of Dosing Solution as determined by laboratory analysis. PFAS Compound Analyte Concentration (ng/L) PFPeA 1,600,000 PFHxA 2,100,000 PFOA 940,000 PFBS 920,000 PFHxS 890,000 PFOS 850,000

Contaminant solution treatments were applied in approximately 100 milliliter (mL) doses to the surface of each column using a syringe such that the solution was distributed relatively even over the soil surface. Dosing was scheduled weekly. When dosing, staff removed any treated textiles or clothing that may have weather, heat, or stain resistant characteristics. In addition, dosing applications and sampling activities were performed after donning a new pair of nitrile gloves. Sampling gloves were exchanged with a new pair at any point the gloves became dirty or contact was made with materials or entities that could have been a potential cross-contaminant source.

Saline treatment plots were irrigated with approximately 100 mL increments of saline irrigation water per week or greater if water levels in the columns allowed. The columns were fertilized weekly with Hoagland complete medium solution (Plant Media Inc.) that supplied plant available N, P, K, Ca, Mg, S, B, Fe, Mn, Zn, Cu, and Mo. The Hoagland's solution was applied at an application rate of approximately 100 mL of a solution prepared as approximately 1.6 grams of Hoagland's solid media per liter of water. The solution was applied to the no-plant control plots as well.

Initial contaminant dosing and salinity dosing of the plants was to begin once the plant species exhibited healthy growth. The phytoremediation experiment was targeted to last 4 months (early November through March 2019); however, vegetation establishment was slow in many cases due to shortened photoperiod (daylength) and winter dormancy. Dosing began on the herbaceous species on Mar. 8, 2019 and the tree species were first dosed on Mar. 14, 2019. When the initial plant tissue sampling took place on Apr. 1, 2019, a total of six doses had been applied to the herbaceous species (i.e., a total of ˜0.6 mg of each PFAS compound applied to each herbaceous column) and a total of five doses had been applied to the tree species (i.e., a total of ˜0.5 mg of each PFAS compound applied to each tree column). The last dosing event was completed on May 8, 2109; at this time a total of twelve doses had been applied to the herbaceous species (i.e., a total of ˜1.2 mg of each PFAS compound applied to each herbaceous column) and a total of eleven doses had been applied to the tree species (i.e., a total of ˜1.1 mg of each PFAS compound applied to each tree column). Final plant tissue sampling was conducted June 6 through Jun. 14, 2019.

For the tree species, samples of the leaves and petioles were collected separately from woody samples of the mainstem and branches. Thus, the laboratory report for the tree species included separate results for leaves/petioles and woody material. Trifolium incamatum (crimson clover) was only sampled during the initial sampling event as the plants underwent senesce prior to the final sampling. In addition, the Fraxinus pennsylvanica (green ash) grew poorly and only three of the six plots generated adequate plant material for collection of leaf/petiole samples.

The tissue samples were collected using clippers that were decontaminated between each sample using the following process:

1. Wiping any attached plant matter from the clippers

2. Washing the clippers in a Liquinox® and deionized water solution

3. Rising the clippers with deionized water

4. Rising the clippers with isopropyl alcohol

5. Rising the clippers again with deionized water.

The samples were containerized in plastic baggies and placed in an iced cooler. Prior to shipping the samples were re-packed on fresh ice and shipped via overnight courier with chain-of-custody documentation and a signed custody seal to the Engineering Research Center (ERC) at Brown University School of Engineering in Providence, Rode Island. With each sample shipment the samples were received in good condition the following morning at the laboratory.

The plant tissue sampling conducted on April 1 occurred only after 24 days of the first dosing event due to the initial deadline date of May 1, 2019 for responding to the Phase II grant solicitation. Hence, the sampling schedule was moved up to accommodate the 30-day laboratory analysis turn-around period. Further, the number of species sampled was limited to ensure the laboratory could process all the submitted samples within 30 days; additional samples would have potentially jeopardized receipt of the sample results in time to respond to the Phase II solicitation. The following six species were sampled:

-   -   Salix nigra (Black Willow)     -   Cynodon dactylon (Bermudagrass)     -   Schedonorus arundinaceus (Tall Fescue)     -   Festuca rubra (Red Fescue)     -   Liquidambar styraciflua (Sweetgum)     -   Trifolium incamatum (Crimson Clover)

Due to the plants reaching maturity (i.e., going to seed), the Brassica juncea (Mustard) and Helianthus annuus (Sunflower) were harvested on Apr. 1, 2019 and stored in a laboratory freezer. On May 14, 2019 the Amaranthus tricolor (Amaranth) plants had reached maturity, were harvested, and stored in the laboratory freezer. The samples stored in the laboratory freezer were shipped to the analytical laboratory along with the final plant samples in June 2019. The final plant tissue sampling was conducted June 6 through Jun. 14, 2019.

Results

From the initial sampling event, a total of 46 samples were analyzed to determine the dry weight concentration of the six contaminant solution compounds: PFOA, PFOS, PFBS, PFPeA, PFHxS, and PFHxA. With the initial laboratory analyses the laboratory reported the detected presence or absence of MeFOSA; MeFOSA presence/absence was not reported with the final laboratory analyses. The sample extraction procedure utilized was based on the procedure by Yoo, et al. (Yoo, H., J. W. Washington, T. M. Jenkins, J. J. Ellington. 2011. Quantitative Determination of Perfluorochemicals and Fluorotelomer Alcohols in Plants from Biosolid-Amended Fields using LC/MS/MS and GC/MS. Environmental Science and Technology, 45, 7985-7990.). The samples were analyzed using an ultra-performance liquid chromatograph (UPLC) equipped with a micro mass spectrometer (MS/MS). The sample results are presented in sequential order in Table 4. The results are reported on a dry weight basis in units of micrograms per kilogram (μg/Kg). The results for MeFOSA are reported as either “Present” or “Absent”.

TABLE 4 PFAS Concentrations in Plant Tissue PFPeA PFBS PFHxA PFHxS PFOA PFOS MeFosa Sample Date Plant Treatment (ug/kg) NAI 1LP Jun. 6, 2019 River Birch No Treatment 7 <1 10 <1 <1 <1 . . . NAI 1W Jun. 6, 2019 River Birch No Treatment <1 <1 <1 <1 <1 <1 . . . NAI 2 Apr. 1, 2019 Black Willow Treatment + Saline 726.2 203.3 207.8 284.4 142.7 9.9 Absent NAI 2LP Jun. 6, 2019 Black Willow Treatment + Saline 19166 260 5569 1533 2530 277 . . . NAI 2W Jun. 6, 2019 Black Willow Treatment + Saline 12 <1 41 15 166 5 . . . NAI 3 Apr. 1, 2019 Crimson Clover Treatment 1351.8 479.3 2255.8 871.2 767.4 125.8 Absent NAI 4 Apr. 1, 2019 Tall Fescue Treatment 1814.2 608.3 3242.5 668 509.2 116.4 Present NAI 4 (100x) Jun. 12, 2019 Tall Fescue Treatment 12850 2698 9776 1408 965 290 . . . NAI 6 Apr. 1, 2019 Sweetgum Control 0.6 <0.4 2.5 2.7 1.8 <0.4 Absent NAI 6LP Jun. 6, 2019 Sweetgum Control 5 <1 17 <1 <1 <1 . . . NAI 6W Jun. 6, 2019 Sweetgum Control <1 <1 <1 <1 <1 <1 . . . NAI 7LP Jun. 6, 2019 Tulip Poplar Treatment 54996 3798 29777 1521 1036 16 . . . NAI 7W Jun. 6, 2019 Tulip Poplar Treatment 3245 46 2014 95 138 11 . . . NAI 9 Apr. 1, 2019 Bermudagrass Treatment 1332.9 851.2 3054.4 1187.9 880.4 332.1 Present NAI 9 (10X) Jun. 12, 2019 Bermudagrass Treatment 4344 1663 4686 572 460 223 . . . NAI 10 Apr. 1, 2019 Bermudagrass No Treatment 280 95 237 25 32 <1 . . . NAI 10 Jun. 12, 2019 Bermudagrass No Treatment 283.1 204.6 952.1 122.7 33.1 <1 Absent NAI 11 Apr. 1, 2019 Sweetgum Treatment 862.2 80.3 1019.4 18 56.3 <0.4 Absent NAI 11LP Jun. 6, 2019 Sweetgum Treatment 248 176 365 277 262 65 . . . NAI 11W Jun. 6, 2019 Sweetgum Treatment 2579 10 849 30 320 27 . . . NAI 12 Apr. 1, 2019 Black Willow Treatment 373.6 62.3 237.9 166 130.7 4.7 Absent NAI 12LP Jun. 6, 2019 Black Willow Treatment 33475 4097 18411 2749 3406 950 . . . NAI 12W Jun. 6, 2019 Black Willow Treatment 370 14 192 37 160 26 . . . NAI 13 Apr. 1, 2019 Sunflower No Treatment <1 <1 <1 1 <1 40 . . . NAI 14 Apr. 1, 2019 Mustard No Treatment <1 <1 1 <1 <1 <1 . . . NAI 15 Apr. 1, 2019 Sunflower No Treatment 538 185 530 281 398 75 . . . NAI 16LP Jun. 6, 2019 Loblolly Pine Treatment 1329 55 147 89 105 12 . . . NAI 16W Jun. 6, 2019 Loblolly Pine Treatment 2 <1 <1 <1 <1 <1 . . . NAI 17LP Jun. 6, 2019 Green Ash No Treatment 55 <1 72 <1 <1 <1 . . . NAI 17W Jun. 6, 2019 Green Ash No Treatment 6 <1 4 <1 <1 <1 . . . NAI 18 Apr. 1, 2019 Red Fescue Treatment + Saline 1812.5 975.3 3601 2412.1 1857.5 624.9 Present NAI 18 (100x) Jun. 12, 2019 Red Fescue Treatment + Saline 36796 13874 39946 9582 9554 2399 . . . NAI 19 Apr. 1, 2019 Crimson Clover No Treatment 3.7 <0.4 17 6.5 1.9 1.5 Absent NAI 20 Apr. 1, 2019 Bermudagrass Treatment + Saline 1517.8 1282 3064.7 1562.5 811.1 239.4 Present NAI 20 (10x) Jun. 12, 2019 Bermudagrass Treatment + Saline 5234 2249 5410 867 767 267 . . . NAI 21 Apr. 1, 2019 Sweetgum Treatment + Saline 74 86 65.1 42.5 4.6 <0.4 Absent NAI 21LP Jun. 6, 2019 Sweetgum Treatment + Saline 193 176 502 946 508 1079 . . . NAI 21W Jun. 6, 2019 Sweetgum Treatment + Saline 111 17 67 30 183 191 . . . NAI 22LP Jun. 7, 2019 River Birch Treatment 21688 908 16399 2257 2994 870 . . . NAI 22W Jun. 7, 2019 River Birch Treatment 1647 4 413 58 135 248 . . . NAI 23 Apr. 1, 2019 Red Fescue No Treatment 5.8 6.1 53.3 14.2 5.6 10.5 Absent NAI 23 Jun. 12, 2019 Red Fescue No Treatment 215 16 143 11 15 <1 . . . NAI 24 Apr. 1, 2019 Red Fescue Treatment 1492 601.2 2738.7 2071.2 1667.4 550.4 Present NAI 24 (100x) Jun. 13, 2019 Red Fescue Treatment 18055 4167 16731 3472 3127 80 . . . NAI 25 Apr. 1, 2019 Tall Fescue No Treatment 5.5 1.8 19.3 4 4.3 6.4 Absent NAI 25 Jun. 13, 2019 Tall Fescue No Treatment 174 6 145 2 8 <1 . . . NAI 26W Jun. 7, 2019 Green Ash Treatment 973 27 338 91 45 6 . . . NAI 27LP Jun. 7, 2019 Tulip Poplar Treatment 60 <1 55 <1 <1 <1 . . . NAI 27W Jun. 7, 2019 Tulip Poplar Treatment 19 <1 4 <1 <1 <1 . . . NAI 28 (100x) May 14, 2019 Amaranth Treatment 47118 253 6347 2593 5551 806 . . . NAI 29 May 14, 2019 Amaranth No Treatment 696 1 334 2 14 <1 . . . NAI 30 (100x) Jun. 13, 2019 Horsetail Treatment 29235 49 23950 304 1693 114 . . . NAI 31LP Jun. 7, 2019 Loblolly Pine No Treatment 5 <1 <1 <1 <1 <1 . . . NAI 31W Jun. 7, 2019 Loblolly Pine No Treatment <1 <1 <1 <1 <1 <1 . . . NAI 32LP Jun. 7, 2019 Sycamore No Treatment 3 <1 6 <1 <1 <1 . . . NAI 32W Jun. 7, 2019 Sycamore No Treatment 1 <1 <1 <1 <1 <1 . . . NAI 33 (100x) Apr. 1, 2019 Mustard Treatment 11888 198 4591 714 1413 344 . . . NAI 34 Jun. 13, 2019 Horsetail No Treatment 241 <1 294 1 9 <1 . . . NAI 35 Apr. 1, 2019 Crimson Clover Treatment 1825.5 844.2 2889.7 459.8 261 0.8 Absent NAI 36LP Jun. 7, 2019 Sycamore Treatment 26615 4776 19306 1774 1802 337 . . . NAI 36W Jun. 7, 2019 Sycamore Treatment 71 <1 63 24 91 33 . . . NAI 37 Apr. 1, 2019 Black Willow No Treatment 0.8 <0.4 0.6 0.6 0.7 0.5 Absent NAI 37LP Jun. 7, 2019 Black Willow No Treatment 126 <1 70 <1 <1 <1 . . . NAI 37W Jun. 7, 2019 Black Willow No Treatment 3 <1 1 <1 <1 <1 . . . NAI 38 Apr. 1, 2019 Bermudagrass Treatment 1177.2 832.7 2747.3 1168.4 699.5 208.5 Present NAI 38 (10x) Jun. 13, 2019 Bermudagrass Treatment 4731 1886 4404 698 745 241 . . . NAI 39 Apr. 1, 2019 Bermudagrass Treatment + Saline 1315.7 1159.9 2975.8 1328.7 628.9 159.6 Present NAI 39 (10x) Jun. 12, 2019 Bermudagrass Treatment + Saline 4914 2127 4290 1068 995 288 . . . NAI 40 Jun. 13, 2019 Horsetail No Treatment 174 5 317 4 13 <1 . . . NAI 41 Apr. 1, 2019 Black Willow No Treatment 0.5 <0.4 <0.4 <0.4 0.5 <0.4 Absent NAI 41LP Jun. 7, 2019 Black Willow No Treatment 31 <1 17 <1 <1 <1 . . . NAI 41W Jun. 7, 2019 Black Willow No Treatment <1 <1 <1 <1 <1 <1 . . . NAI 42W Jun. 7, 2019 Loblolly Pine Treatment 5 <1 7 2 8 3 . . . NAI 42LP Jun. 7, 2019 Loblolly Pine Treatment 880 64 106 111 190 25 . . . NAI 44 Apr. 1, 2019 Red Fescue Treatment + Saline 1260.5 529.3 2030.9 1637.7 1136.7 546.1 Present NAI 44 (100x) Jun. 13, 2019 Red Fescue Treatment + Saline 17155 4384 19130 3816 3456 1399 . . . NAI 45 May 14, 2019 Amaranth No Treatment 17 <1 93 <1 2 <1 . . . NAI 46LP Jun. 7, 2019 Green Ash No Treatment 57 7 59 4 <1 <1 . . . NAI 46W Jun. 7, 2019 Green Ash No Treatment 4 <1 1 <1 <1 <1 . . . NAI 47LP Jun. 7, 2019 Tulip Poplar Treatment 35075 28428 19919 4428 1743 1620 . . . NAI 47W Jun. 7, 2019 Tulip Poplar Treatment 1743 51 1529 58 51 44 . . . NAI 48 (10x) Apr. 1, 2019 Sunflower Treatment 6494 191 1963 330 395 90 . . . NAI 49 Apr. 1, 2019 Tall Fescue No Treatment 4.8 3 24.4 5.4 7.3 10.2 Absent NAI 49 Jun. 13, 2019 Tall Fescue No Treatment 185 48 179 8 11 2 . . . NAI 50 (100x) May 14, 2019 Amaranth Treatment 64183 324 23866 3185 7039 754 . . . NAI 51 Apr. 1, 2019 Sweetgum Treatment + Saline 263.6 96.5 217.7 29.4 7.8 <0.4 Absent NAI 51LP Jun. 7, 2019 Sweetgum Treatment + Saline 16645 4355 11189 5393 4534 3840 . . . NAI 51W Jun. 7, 2019 Sweetgum Treatment + Saline 388 64 234 24 144 202 . . . NAI 52 Apr. 1, 2019 Black Willow Treatment 795.8 229.3 382.6 316 292.9 16.9 Absent NAI 52LP Jun. 7, 2019 Black Willow Treatment 25191 378 17343 2049 3877 413 . . . NAI 52W Jun. 7, 2019 Black Willow Treatment 521 12 248 85 339 53 . . . NAI 53 Apr. 1, 2019 Mustard No Treatment <1 <1 <1 <1 <1 <1 . . . NAI 54 Apr. 1, 2019 Tall Fescue Treatment 1011.7 488.3 1906.4 377.6 267.5 61.4 Present NAI 54 (10x) Jun. 13, 2019 Tall Fescue Treatment 4971 2105 4273 870 614 114 . . . NAI 55 Apr. 1, 2019 Sycamore Treatment 1390.1 486 2105.3 1490.4 1143.7 432.8 Present NAI 55 (100x) Jun. 13, 2019 Sycamore Treatment 25465 5427 21402 5166 4465 1730 . . . NAI 56LP Jun. 7, 2019 Sycamore Treatment 11442 143 3212 296 431 46 . . . NAI 56W Jun. 7, 2019 Sycamore Treatment 113 5 47 14 46 <1 . . . NAI 57LP Jun. 7, 2019 Loblolly Pine No Treatment 14 <1 <1 <1 <1 <1 . . . NAI 57W Jun. 7, 2019 Loblolly Pine No Treatment <1 <1 <1 <1 <1 <1 . . . NAI 58 (100x) Apr. 1, 2019 Mustard Treatment 20412 2411 16550 1783 2684 638 . . . NAI 59 Apr. 1, 2019 Bermudagrass No Treatment 5.1 <0.4 12.6 1.1 1.4 1.6 Absent NAI 59 Jun. 12, 2019 Bermudagrass No Treatment 110 18 78 <1 1 <1 . . . NAI 61LP Jun. 10, 2019 River Birch No Treatment 5 <1 17 <1 <1 <1 . . . NAI 61W Jun. 10, 2019 River Birch No Treatment 2 <1 <1 <1 <1 <1 . . . NAI 62 Apr. 1, 2019 Sweetgum No Treatment 1.1 <0.4 2.6 <0.4 0.4 <0.4 Absent NAI 62LP Jun. 7, 2019 Sweetgum No Treatment 26 <1 75 <1 <1 <1 . . . NAI 62W Jun. 7, 2019 Sweetgum No Treatment <1 <1 <1 <1 <1 <1 . . . NAI 63 Jun. 13, 2019 Red Fescue No Treatment 344 3 191 3 7 <1 . . . NAI 63 Apr. 1, 2019 Red Fescue No Treatment 2.5 1.4 44.6 1.8 3.3 2.2 Absent NAI 64 (100x) Jun. 14, 2019 Horsetail Treatment 30180 40 19789 276 1263 190 . . . NAI 65 Apr. 1, 2019 Sunflower No Treatment <1 6 2 31 11 267 . . . NAI 66W Jun. 1, 2019 Green Ash Treatment 92 187 23 167 22 55 . . . NAI 67LP Jun. 7, 2019 Tulip Poplar No Treatment 11 7 12 <1 <1 <1 . . . NAI 67W Jun. 7, 2019 Tulip Poplar No Treatment 5 <1 <1 <1 <1 <1 . . . NAI 68 Apr. 1, 2019 Crimson Clover No Treatment 5 <0.4 15.7 0.6 0.4 <0.4 Absent NAI 69 (100x) Jun. 14, 2019 Horsetail Treatment 36682 32 26854 257 1644 203 . . . NAI 70 Apr. 1, 2019 Crimson Clover Treatment 1307.7 393.2 2333.5 413.1 318.3 <0.4 Absent NAI 71 Apr. 1, 2019 Sweetgum Treatment 231.6 106.5 196.3 31.4 48.8 <0.4 Absent NAI 71LP Jun. 11, 2019 Sweetgum Treatment 5665 414 3047 1977 3226 942 . . . NAI 71W Jun. 11, 2019 Sweetgum Treatment 97 6 53 55 336 132 . . . NAI 72LP Jun. 11, 2019 Sycamore No Treatment 11 <1 30 <1 <1 <1 . . . NAI 72W Jun. 11, 2019 Sycamore No Treatment 3 <1 <1 <1 <1 <1 . . . NAI 73 Jun. 14, 2019 Red Fescue No Treatment 86 1 58 <1 1 <1 . . . NAI 73 Apr. 1, 2019 Red Fescue No Treatment 3.1 1.5 8.4 4.3 4.9 5.4 Absent NAI 74 Apr. 1, 2019 Tall Fescue No Treatment 3.9 1 13 1 2.2 1.4 Absent NAI 74 Jun. 14, 2019 Tall Fescue No Treatment 231 6 145 2 13 <1 . . . NAI 75 (10x) May 14, 2019 Amaranth Treatment 3061 401 10089 2817 4731 348 . . . NAI 76 Apr. 1, 2019 Black Willow Treatment + Saline 696.5 102.4 229 160 123.1 <0.4 Absent NAI 76LP Jun. 11, 2019 Black Willow Treatment + Saline 25291 454 15064 2264 2656 376 . . . NAI 76W Jun. 11, 2019 Black Willow Treatment + Saline 23 <1 32 7 107 <1 . . . NAI 77LP Jun. 11, 2019 River Birch Treatment 32796 1135 23620 3137 5936 1391 . . . NAI 77W Jun. 11, 2019 River Birch Treatment 274 4 156 17 159 30 . . . NAI 80 Apr. 1, 2019 Mustard No Treatment 14 <1 9 <1 <1 <1 . . . NAI 81LP Jun. 11, 2019 River Birch Treatment 31005 1362 20210 3704 7326 3015 . . . NAI 81W Jun. 11, 2019 River Birch Treatment 138 <1 91 50 239 263 . . . NAI 82LP Jun. 11, 2019 Loblolly Pine Treatment 682 5 25 13 19 <1 . . . NAI 82W Jun. 11, 2019 Loblolly Pine Treatment 2 <1 2 <1 <1 <1 . . . NAI 83 Apr. 1, 2019 Bermudagrass No Treatment 2.5 <0.4 3.1 1.4 1.4 1.9 Absent NAI 83 Jun. 13, 2019 Bermudagrass No Treatment 103 12 72 4 1 <1 . . . NAI 84 (10x) Apr. 1, 2019 Mustard Treatment 6789 944 3944 409 1348 319 . . . NAI 85 (10x) Apr. 1, 2019 Sunflower Treatment 4779 159 407 217 291 68 . . . NAI 86LP Jun. 11, 2019 Loblolly Pine No Treatment 7 <1 <1 <1 <1 <1 . . . NAI 86W Jun. 11, 2019 Loblolly Pine No Treatment <1 <1 <1 <1 <1 <1 . . . NAI 87LP Jun. 11, 2019 Sycamore No Treatment 28 <1 26 <1 <1 <1 . . . NAI 87W Jun. 11, 2019 Sycamore No Treatment 2 <1 <1 <1 <1 <1 . . . NAI 88 Jun. 14, 2019 Horsetail No Treatment 297 3 307 3 17 <1 . . . NAI 89 Apr. 1, 2019 Red Fescue Treatment 1121.3 582.2 2156.7 1791.7 1417.1 608.8 Present NAI 89 (100x) Jun. 14, 2019 Red Fescue Treatment 22127 9823 21127 4293 3618 1627 . . . NAI 90 Apr. 1, 2019 Red Fescue Treatment + Saline 2651.4 758.7 2804.6 2148.9 1597.9 719.8 Present NAI 90 (100x) Jun. 14, 2019 Red Fescue Treatment + Saline 19490 3767 16710 3703 3141 1815 . . . NAI 91LP Jun. 11, 2019 Green Ash Treatment 169 816 690 1353 <1 <1 . . . NAI 91W Jun. 11, 2019 Green Ash Treatment 73 14 26 4 1 <1 . . . NAI 92 Apr. 1, 2019 Black Willow Treatment 656.7 136.6 204.6 197.9 170.8 5.3 Absent NAI 92LP Jun. 11, 2019 Black Willow Treatment 36271 5337 21250 2889 3043 306 . . . NAI 92W Jun. 11, 2019 Black Willow Treatment 230 6 117 47 225 17 . . . NAI 93 May 14, 2019 Amaranth No Treatment 204 2 186 11 15 116 . . . NAI 94 Apr. 1, 2019 Bermudagrass Treatment 1145.9 778.1 2736.3 1129.5 840.3 320.3 Present NAI 94 (10x) Jun. 13, 2019 Bermudagrass Treatment 4852 1467 4634 396 559 197 . . . NAI 95 Apr. 1, 2019 Sunflower No Treatment 24 2 11 7 8 52 . . . NAI 96LP Jun. 11, 2019 Black Willow No Treatment 43 <1 33 <1 <1 <1 . . . NAI 96W Jun. 11, 2019 Black Willow No Treatment 12 <1 3 <1 <1 <1 . . . NAI 97LP Jun. 11, 2019 Sycamore Treatment 15456 252 5163 834 1136 404 . . . NAI 97W Jun. 11, 2019 Sycamore Treatment 66 1 54 6 52 14 . . . NAI 98 Apr. 1, 2019 Crimson Clover No Treatment 2.5 0.6 7 0.4 0.6 <0.4 Absent NAI 99 Apr. 1, 2019 Tall Fescue Treatment 1015 492.6 1777.3 433.8 367.9 60.6 Present NAI 99 (100x) Jun. 14, 2019 Tall Fescue Treatment 26518 9371 23988 2769 1722 388 . . . NAI100 Apr. 1, 2019 Bermudagrass Treatment + Saline 1302.3 1142.2 2234.6 1545.6 985.6 263.2 Present NAI 100 (10x) Jun. 13, 2019 Bermudagrass Treatment + Saline 4804 1564 4164 622 690 286 . . . NAI101 Apr. 1, 2019 Sweetgum Treatment 1254.4 142.6 1311.5 145.4 175.3 <0.4 Absent NAI 101LP Jun. 11, 2019 Sweetgum Treatment 298 335 531 557 501 168 . . . NAI 101W Jun. 11, 2019 Sweetgum Treatment 268 6 147 37 406 56 . . . NAI 102LP Jun. 11, 2019 Tulip Poplar Treatment 17853 18407 4119 3032 1366 805 . . . NAI 102W Jun. 11, 2019 Tulip Poplar Treatment 189 8 233 15 22 31 . . . NAI 103LP Jun. 12, 2019 Black Willow Treatment + Saline 39416 544 15533 4999 4771 2670 . . . NAI 103W Jun. 12, 2019 Black Willow Treatment + Saline 177 2 100 97 381 180 . . . NAI 104LP Jun. 12, 2019 River Birch No Treatment 79 12 71 28 76 6 . . . NAI 104W Jun. 12, 2019 River Birch No Treatment <1 <1 <1 <1 <1 <1 . . . NAI105 Apr. 1, 2019 Sweetgum Treatment + Saline 415.7 65.9 705.1 70.4 69.9 <0.4 Absent NAI 105LP Jun. 12, 2019 Sweetgum Treatment + Saline 4064 386 2720 2239 2372 359 . . . NAI 105W Jun. 12, 2019 Sweetgum Treatment + Saline 208 10 155 39 310 101 . . . NAI 106W Jun. 12, 2019 Green Ash No Treatment 2 <1 <1 <1 <1 <1 . . . NAI 107LP Jun. 12, 2019 Tulip Poplar No Treatment 7 <1 4 <1 <1 <1 . . . NAI 107W Jun. 12, 2019 Tulip Poplar No Treatment 4 <1 <1 <1 <1 <1 . . . NAI108 Apr. 1, 2019 Sweetgum No treatment 1.1 <0.4 2.6 <0.4 0.7 <0.4 Absent NAI 108LP Jun. 12, 2019 Sweetgum No treatment 15 <1 50 <1 <1 <1 . . . NAI 108W Jun. 12, 2019 Sweetgum No treatment <1 <1 <1 <1 <1 <1 . . .

Table 5 presents the average final sampling results by species and treatment (except crimson clover, mustard, and sunflower which were all sampled only once at the initial sampling event). Of the herbaceous species, the highest average plant tissue concentrations were observed in Festuca rubra (Red Fescue) that received contaminant treatments with saline irrigant. An exception is for PFOA, where Amaranthus (Amaranth) showed the highest average concentration of PFOA. Of the tree species, the highest average plant tissue concentrations were observed in Betula nigra-LP (River Birch-LP), except for PFBS where Liriodendron tulipifera-LP (Tulip Poplar-LP) showed the highest average. Along with Betula nigra-LP and Liriodendron tulipifera-LP, Liquidambar styraciflua-LP (Sweetgum-LP) and Salix nigra-LP (Black Willow-LP) showed higher overall accumulations of PFAS compounds, though at slightly lower averages.

The Cynodon dactylon (Bermudagrass) control column NAI 10, was inadvertently dosed on March 22 with approximately 70 mL of contaminant solution. The data from NAI 10 was not utilized in calculating average values presented in Table 5.

TABLE 5 Average PFAS concentrations in final plant tissue samples for each species and treatment. PFBS PFPeA PFHxA PFHxS PFOA PFOS Plant Type Treatment (μg/Kg) (μg/Kg) (μg/Kg) (μg/Kg) (μg/Kg) (μg/Kg) Liquidambar Control <1 15.3 47.3 <1 <1 <1 styraciflua-LP Treatment 308.3 2070.3 1314.3 937.0 1329.7 391.7 Treatment + Saline 1639.0 6967.3 4803.7 2859.3 2471.3 719.0 Liquidambar Control <1 <1 <1 <1 <1 <1 styraciflua-W Treatment 7.3 981.3 349.7 40.7 354.0 71.7 Treatment + Saline 30.3 235.7 152.0 31.0 212.3 164.7 Salix nigra-LP Control 0.0 66.7 40.0 <1 <1 <1 Treatment 3270.7 31645.7 19001.3 2562.3 3442.0 556.3 Treatment + Saline 419.3 27957.7 12055.3 2932.0 3319.0 1107.7 Salix nigra-W Control <1 5.0 1.3 <1 <1 <1 Treatment 10.7 373.7 185.7 56.3 241.3 32.0 Treatment + Saline 0.7 70.7 57.7 39.7 218.0 61.7 Liriodendron Control 2.3 26.0 23.7 <1 <1 <1 tulipifera-LP Treatment 16877.7 35974.7 17938.3 2993.7 1381.7 813.7 Liriodendron Control 29.5 650.3 588.7 36.5 36.5 37.5 tulipifera-W Treatment 46.0 1084.7 2014.0 95.0 138.0 11.0 Plantanus Control 0.0 14.0 20.7 0.0 0.0 0.0 occidentalis-LP Treatment 1723.7 17837.7 9227.0 968.0 1123.0 262.3 Plantanus Control <1 2.0 <1 <1 <1 <1 occidentalis-W Treatment 2.0 83.3 54.7 14.7 63.0 15.7 Pinus taeda-LP Control <1 8.7 <1 <1 <1 <1 Treatment 41.3 963.7 92.7 71.0 104.7 12.3 Pinus taeda-W Control <1 <1 <1 <1 <1 <1 Treatment <1 3.0 3.0 0.7 2.7 1.0 Fraxinus Control 3.5 56 65.5 2.0 <1 <1 pennsylvanica-LP Treatment 816.0 169.0 690.0 1353.0 <1 <1 Fraxinus Control <1 4.0 1.7 <1 <1 <1 Pennsylvania-W Treatment 76.0 379.3 129.0 87.3 22.7 20.3 Betula nigra-LP Control 4.0 30.3 32.7 9.3 25.3 2.0 Treatment 1135.0 28496.3 20076.3 3032.7 5418.7 1758.7 Betula nigra-W Control <1 0.7 <1 <1 <1 <1 Treatment 2.7 686.3 220.0 41.7 177.7 180.3 Festuca Rubra Control 6.7 215.0 130.7 4.7 7.7 0.0 Treatment 6472.3 21882.3 19753.3 4310.3 3736.7 1145.7 Treatment + Saline 7341.7 24480.3 25262.0 5700.3 5383.7 1871.0 Cynodon Control 15.0 75.0 1.0 2.0 1.0 <1 Dactylon Treatment 1672.0 4574.7 588.0 555.3 588.0 220.3 Treatment + Saline 1980.0 4621.3 817.3 852.3 817.3 280.3 Trifolium Control 3.7 0.6 13.2 2.5 1.0 0.5 incarnatum* Treatment 1495.0 572.2 2493.0 581.4 448.9 42.2 Schedonorus Control 20.0 196.7 156.3 4.0 10.7 0.7 arundinaceus Treatment 4724.7 14779.7 12679.0 1682.3 1100.3 264.0 Helianthus annus Control 4.0 24.0 6.5 13.0 9.5 119.7 Treatment 178.3 3937.0 966.7 276.0 361.3 77.7 Brassica juncea Control <1 4.7 3.0 <1 <1 <1 Treatment 1184.3 13029.7 8361.7 968.7 1815.0 433.7 Amaranthus Control 1.5 305.7 204.3 6.5 10.3 38.7 tricolor Treatment 326.0 38120.7 13434.0 2865.0 5773.7 636.0 Equisetum Control 4.0 237.3 306.0 2.7 13.0 0.0 hyemale Treatment 40.3 32032.3 23531.0 279.0 1533.3 169.0

In assessing the fitness of plant species to serve in a phytoremediation role by means of phytoextraction, the Bioconcentration Factor (BCF) is a key metric. The BCF is calculated as the plant/soil contaminant concentration ratio: BCF_(plant) =C _(plant) /C _(reference media)

A BCF that is >1 is considered to indicate accumulation. However, for use in a phytoextraction context, it is ideal for remedial plants to have a BCF of 10 or more. An additional criterion of note is when a plant accumulates an amount of a substance (i.e., contaminant) that is two orders of magnitude greater accumulation than that found in plants growing in uncontaminated media. A plant meeting these criteria is considered a hyperaccumulator (McCutcheon, et al., 2003).

BCFs were calculated for each contaminant for all species. The soil PFAS concentrations were calculated based on the measured volumes of soil in the columns and the amount of contaminant solution dosed. In calculating the soil concentrations, the nominal concentrations of PFAS compounds dosed were adjusted per the dosing solution laboratory results (Table 3). FIGS. 2 through 22 present bar graphs showing the calculated BCFs for each herbaceous species and each tree species (leaf-petiole tissue samples) for each contaminant.

With respect to the higher profile PFAS compounds (PFOS, PFOA, PFBS) the following species showed BCF concentrations >10 for one or more: Festuca Rubra (Red Fescue), Betula nigra-LP (River Birch-LP), Liquidambar styraciflua-LP (Sweetgum-LP), Salix nigra-LP (Black Willow-LP), Plantanus occidentalis-LP (Sycamore-LP), Liriodendron tulipifera-LP (Tulip Poplar-LP), Amaranthus tricolor (Amaranth), Schedonorus arundinaceus (Tall Fescue), Cynodon Dactylon (Bermudagrass), Brassica juncea (Mustard), Equisetum hyemale (Horsetail). With respect to the tree species, hyperaccumulation was observed in the leaves and petioles and not in the woody mass (mainstems and branches). The BCFs for these compounds are summarized in Table 6.

TABLE 6 Species exhibiting BCFs greater than 10. BCF BCF Saline BCF Species Compound Treatment Treatment Control River Birch - LP PFOS 16.4 — 0 Red Fescue 11 17.9 0 Sweetgum - LP 3.6 16   0 Black Willow - LP 5.2 10.3 0 Amaranth PFOA 45 — 0.1 Horsetail 12.1 — 0.1 Mustard 14.1 — 0 River Birch - LP 45.8 — 0.2 Sweetgum - LP 10.9 20.3 0 Red Fescue 32.3 46.5 0.1 Black Willow - LP 28.9 27.9 0 Tulip Poplar - LP 11.5 — 0 Sweetgum - LP PFBS 2.6 13.8 0 Black Willow - LP 28.1  3.6 0 Bermudagrass 14 16.5 0.1 Red Fescue 57.2 64.9 0.1 Sycamore - LP 15.2 — 0 Tulip Poplar - LP 143.7 — 0 Tall Fescue 39.6 — 0.2 — = Treatment Not Tested LP = leaves and petioles

Discussion

Our results establish Proof-of-Concept for phytoremediation of multiple PFAS compounds. Festuca rubra (Red Fescue) preformed the best overall at contaminant accumulation and achieved hyperaccumulation of all six PFAS compounds including PFOA, PFOS, and PFBS over the course of the study (as well as after 24 days from initial contaminant dosing when the first sampling event was completed on Apr. 1, 2018) in both the contaminant treatment and the contaminant+salinity treatment. The average red fescue BCF of the contaminant+salinity treatment showed greater accumulation than the treatment only for all six PFAS compounds. The final contaminant+salinity treatment samples had BCFs that ranged from approximately 17.9 (PFOS) to approximately 124.4 (PFPeA). The contaminant treatment had BCFs that ranged from approximately 11.0 (PFOS) to approximately 111.2 (PFPeA).

The large difference in PFAS accumulation between red fescue (Festuca rubra) compared to tall fescue (Schedonorus arundinaceus) is notable. However, there has been controversy regarding the naming and classification of the fescues (Casler, et al. 2008). The fine fescues, such as red fescue, are classified in the genus Festuca. The broadleaf fescues, such as tall fescue, were originally grouped into Festuca. As the science of plant classification developed and became more sophisticated, the broadleaf fescues were given their own genus: Schedonorus (Casler, et al. 2008). Hence, differences in accumulation of PFAS coincide with significant differences with the two plant species.

In addition to the red fescue, the leaves and petioles associated with the contaminant+salinity treatment for Liquidambar styraciflua (Sweetgum-LP) achieved hyperaccumulation of all six PFAS compounds. The contaminant+salinity treatment samples had BCFs that ranged from approximately 13.8 (PFBS) to approximately 33.7 (PFPeA). The woody samples showed negligible PFAS concentrations.

As a species, the black willow leaves and petioles achieved hyperaccumulation of all six PFAS compounds, but not within the same treatment. Black willow leaves and petioles achieved hyperaccumulation for the contaminant+salinity treatment for all but PFBS, whereas, they achieved hyperaccumulation for the contaminant only treatment for all but PFOS. The woody samples showed negligible PFAS concentrations.

River birch leaves and petioles showed hyperaccumulation for all but PFBS, but the BCF for PBFS was approximately 9.8. River birch leaves and petioles had the highest BCF for PFOA in study with a value of approximately 45.8. The woody samples showed negligible PFAS concentrations.

Like river birch, tulip poplar leaves and petioles showed hyperaccumulation for all but PFOS, but the BCF for PFOS was approximately 7.5. Tulip poplar leaves and petioles had the highest BCF for any of the tested PFAS compounds with a value of approximately 176.1 for PFPeA. The woody samples showed negligible PFAS concentrations.

Although Amaranthus did not achieve hyperaccumulation for PFBS or PFOS, it did hyperaccumulate the remaining four PFAS compounds and had one of the highest BCFs for PFOA (approximately 45.0).

Given Festuca rubra is shade tolerant and its growing seasons are spring and fall (i.e., cool season grass), its use with a successfully hyperaccumulating deciduous tree species is suited to work in tandem. This approach would involve a double-canopy system or a double cropping system. A double-canopy system entails management of two remedial crops, whereby the cool season red fescue grass grows during the fall and spring and a deciduous tree species (e.g., willow, sweetgum, river birch, tulip poplar) is grown to a degree of maturity. In this scenario the trees break winter dormancy and begin to leaf-out just as the growth of the red fescue crop peaks, is harvested, and then grass growth declines as summer temperatures increase.

A double cropping system using red fescue and a deciduous tree species entails a somewhat more innovative approach. This approach uses elements of an intensive forest management technique of short or ultrashort rotation coppice (SRC). The SRC silviculture practice contemplated in this approach involves annual harvests using a system principally associated with maximizing woody biomass production as a bioenergy crop (Hauk, et al., 2014). Early development of short-rotation forest management techniques and systems were initially developed to a thorough degree in the 1970s when an energy crisis and pulp & paper demands necessitated innovations to meet national needs and industrial demands (Steinbeck, 1972; EPA, 1978). These management systems have been further refined since, and SRC has experienced renewed focus as concerns and costs associated with fossil fuel and climate change have intensified (Hauk, et al., 2014). With these systems both red fescue and the annual growth of managed saplings are both mechanically harvested. Ultrashort SRC, where hardwoods are harvested annually with power scythes, has been referred to as “wood grass”; it has been shown to be technologically and economically feasible (Kopp, et al., 1993). Hence, the use of cool season red fescue in combination with wood grass has merit. With such an approach red fescue would be harvested as the tree crop emerges from dormancy and the hardwood “wood grass” would be harvested in late summer or early autumn before leaf fall. With SRC, hardwoods regenerate each year from coppice and the need for replanting to replace mortality is manageable, even with annual harvests (e.g., <30% to 50% mortality after five successive annual harvests) (Kopp, et al., 1993). Vigorous regeneration from coppice stools can often persist beyond 30 years (Kopp, et al., 1993).

In this study, the growth media consisted of low ionic exchange screened sand with little organic matter. This growth media generated conditions where the PFAS compounds were more readily available for plant uptake than would be found in a typical field situation. However, the rationale supporting the use of a salinity treatment is that it should increase plant uptake of PFAS, which is supported by our results, because a saline solution, such as one containing divalent calcium and magnesium salts, creates greater ionic strength within the soil solution and helps displace PFAS compounds bound to soil exchange sites and organic matter. This increases the PFAS compounds in the soil solution, rendering them more available for plant uptake.

We note that our target soil salinity was approximately 4,000 μS/cm, which is the level that defines a saline soil condition. However, the saline-treated plants utilized are reportedly tolerant of this salinity level. The salinity level was raised incrementally during the study with regular doses of the saline treatment. The rate of increase in soil salinity levels was more gradual and slower than anticipated. During the study, soil conductivity measurements were made using a direct soil conductivity meter. At the time of the final plant sampling, the control and treatment soils had soil electrical conductivity levels of approximately 50 to approximately 100 μS/cm; the treatment+saline soils had an average conductivity of approximately 1,220 μS/cm. Thus, with further increases in soil salinity greater increases in PFAS uptake by the plants may occur than achieved in this study.

The screened and washed sand used as the growth media in our study was low in organic matter; although, the grasses and legumes that were used in the study were first propagated from seed in shallow trays of potting soil which contributed some organic matter content when these plants were transplanted into the columns. Nevertheless, the plants were grown in a relatively low organic matter medium. We understand the plants uptake PFAS with uptake of soil-water. If impacted sites are managed such that organic matter and soluble carbon are reduced, then a concomitant increase in uptake rates of PFAS by plants will occur. Site management that includes elements of tillage and application of synthetic inorganic nitrogen fertilizer are strategies to lower soil carbon levels and increase PFAS phytoextraction. When combined with salinity treatments, some of the negative effects of reduced soil organic matter, particularly in loamy or clayey soils, can be lessened by the beneficial flocculating effect of the divalent cations calcium and magnesium.

The higher concentrations of PFAS in the forage grass is also understood to be partially related to the protein content in the plant tissue, as some researchers exploring PFAS prevalence in agricultural crops have found higher PFAS concentrations correlating positively with higher protein contents. Harvesting younger growth on a more frequent harvest schedule, like that which drives greater nitrogen assimilation on nitrogen-limiting land treatment sites, is a strategy applicable to driving increased PFAS assimilation within a phytoremediation context.

Festuca species are cool season grasses that are best planted in the autumn and harvested in spring, before deciduous trees fully leaf out. Festuca can be propagated from seed and yields can typically meet amounts of approximately 3 tons per acre or more. With ultrashort SRC systems yields can average approximately 10 oven-dry tons per hectare per year (o.d. t ha⁻¹y⁻¹) with fertilization. For example, one study reported production capacities of various willow tree species ranged from approximately 8.0 to approximately 15.5 o.d. t ha⁻¹yr⁻¹ over a multiyear study (Kopp, et al., 1993). At such rates of agronomic/forest production, along with the ability to mechanically cultivate and harvest, the viability of phytoextraction of PFAS from contaminated soil and sediment is practical and a “greener cleanup” technology in that it meets core elements outlined in the American Society of Testing Materials (ASTM) E2893 Standard Guide for Greener Cleanups that include minimizing greenhouse gas emissions, air pollutants, use of materials, generation of waste, disturbance to land and ecosystems, and noise and light disturbance. This is particularly the case on sites where PFAS concentrations are at moderate to lower levels and where the size of the impacted area is large (>1 acre).

As an example, a cubic foot of soil that is similar to the tested growth media and having concentrations of approximately 110 ug/Kg (ppb) of PFOS and PFOA that undergoes phytoremediation with red fescue and utilizing salinity enhancement, it is estimated it would take approximately 10 years and approximately 3.5 years to reduce the concentrations of PFOS and PFOA by approximately 50%, respectively. However, if red fescue is utilized in tandem in a double cropping system, this time frame could potentially be reduced by approximately 30%.

Overall, our results demonstrate the feasibility of remediating PFAS contaminated sites. We seek to protect our viable intellectual property via patent protections.

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The term “approximately”/“approximate” can be +/−10% of the amount referenced. Additionally, preferred amounts and ranges can include the amounts and ranges referenced without the prefix of being approximately.

Although specific advantages have been enumerated above, various embodiments may include some, none, or all of the enumerated advantages.

Modifications, additions, or omissions may be made to the systems, apparatuses, and methods described herein without departing from the scope of the disclosure. For example, the components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses disclosed herein may be performed by more, fewer, or other components and the methods described may include more, fewer, or other steps. Additionally, steps may be performed in any suitable order. As used in this document, “each” refers to each member of a set or each member of a subset of a set.

To aid the Patent Office and any readers of any patent issued on this application in interpreting the claims appended hereto, applicants wish to note that they do not intend any of the appended claims or claim elements to invoke 35 U.S.C. 112(f) unless the words “means for” or “step for” are explicitly used in the particular claim.

While the invention has been described, disclosed, illustrated and shown in various terms of certain embodiments or modifications which it has presumed in practice, the scope of the invention is not intended to be, nor should it be deemed to be, limited thereby and such other modifications or embodiments as may be suggested by the teachings herein are particularly reserved especially as they fall within the breadth and scope of the claims here appended. 

We claim:
 1. A method for increasing the amount of per- and polyfluoroalkyl substances (PFAS) that a plant will accumulate from PFAS contaminated media, soil, sediment, and groundwater, comprising the steps of: growing live selected plants in per- and polyfluoroalkyl substances (PFAS) contaminated media, soil, sediments, or groundwater; and providing for phytoremediation via phytoextraction of the per- and polyfluoroalkyl substances (PFAS) from the contaminated media, soil, sediments or the groundwater, wherein the providing step further includes managing soil salinity levels to increase ionic strength and salinity of the contaminated media, soil, sediments and ground water with _CaSO₄.2H₂O to increase the ionic strength and salinity of the contaminated media to have a salinity of approximately 1,220 μS/cm.
 2. A method for increasing the amount of per- and polyfluoroalkyl substances (PFAS) that a plant will accumulate from PFAS contaminated media, soil, sediment, and groundwater, comprising the steps of: growing live selected plants in per- and polyfluoroalkyl substances (PFAS) contaminated media, soil, sediments, or groundwater; and providing for phytoremediation via phytoextraction of the per- and polyfluoroalkyl substances (PFAS) from the contaminated media, soil, sediments or the groundwater, wherein the providing step further includes managing soil salinity levels to increase ionic strength and salinity of the contaminated media, soil, sediments and ground water with MgSO₄.2H₂O to increase the ionic strength and salinity of the contaminated media to have a salinity of approximately 1,220 μS/cm.
 3. A method for increasing the amount of per- and polyfluoroalkyl substances (PFAS) that a plant will accumulate from PFAS contaminated media, soil, sediment, and groundwater, comprising the steps of: growing live selected plants in per- and polyfluoroalkyl substances (PFAS) contaminated media, soil, sediments, or groundwater; and providing for phytoremediation via phytoextraction of the per- and polyfluoroalkyl substances (PFAS) from the contaminated media, soil, sediments or the groundwater, wherein the providing step further includes managing soil salinity levels to increase ionic strength and salinity of the contaminated media, soil, sediments and ground water with MgSO₄.2H₂O to increase the ionic strength and salinity of the contaminated media to have a salinity of approximately 4,000 μS/cm.
 4. A method for increasing the amount of per- and polyfluoroalkyl substances (PFAS) that a plant will accumulate from PFAS contaminated media, soil, sediment, and groundwater, comprising the steps of: growing live selected plants in per- and polyfluoroalkyl substances (PFAS) contaminated media, soil, sediments, or groundwater; and providing for phytoremediation via phytoextraction of the per- and polyfluoroalkyl substances (PFAS) from the contaminated media, soil, sediments or the groundwater, wherein the providing step further includes managing soil salinity levels to increase ionic strength and salinity of the contaminated media, soil, sediments and ground water with CaSO₄.2H₂O to increase the ionic strength and salinity of the contaminated media to have a salinity of approximately 4,000 μS/cm. 